Re: Big odds ration in binary regression output

Posted by Rich Ulrich on Aug 24, 2017; 3:07am
URL: http://spssx-discussion.165.s1.nabble.com/Big-odds-ratio-in-binary-regression-output-tp5734731p5734755.html

There is a limit to how big a correlation you can expect between scaled variables.

In my experience, two items scored on a Likert-type scale are effectively measuring

the same thing when their r is 0.80.  The only way it gets higher is by artifact and

"shared error".  For two dichotomies, I expect the same underlying trait when

their r is 0.60.  The max is lower when their skews are not synchronized.  Dichotomous

r's of 0.40 are large.

What is special about the question, "... are you satisfied with the services... ", is

that hospital administrators have learned to respect it.  It is now /the/ popular

measure of outcome.  To me, both your highest item and its composite seem to

measure that same outcome - as a latent trait.  So, yes, you still get a high OR.

And the question I have:  What are you trying to learn, or to accomplish?

Given the classical question ("satisfied") and one or two or three alternate

versions (item with r=0.61; item with r=0.56; composite score), I think I would

want to examine the discordant answers - Why does someone say Yes to "satisfied"

while saying No to "took care of you"?  (and vice-versa.)  That's what occurs to

me, but  don't know what other sort of data you have available, or what your

mandate is for these data.

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Rich Ulrich

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From: SPSSX(r) Discussion <[hidden email]> on behalf of Sidra <[hidden email]>
Sent: Wednesday, August 23, 2017 2:05:13 PM
To: [hidden email]
Subject: Re: Big odds ration in binary regression output

 

Eugene and Ulrich, thanks for your valuable suggestions. I have tried looking
at the individual items of the problem predictor variable "Interpersonal
communication and care" and their correlations with DV through Phi
correlations (individual items were measured at binary level). It seems that
the items which pertain to interpersonal care for instance "were you treated
with respect and courtesy?" have high correlations with DV  (.4 to
.61)whereas the items of this same factor which pertain to communication
part such as "were you given sufficient information regarding care of the
newborn?" have moderate correlation with DV( ranging from .2 to .4). I want
you to note that the DV was measured using a single item worded as "All in
all, were you satisfied with the services you received during your stay in
the hospital?" with response options of yes and no. As far as I can think, I
don't see any replication of ideas here. But one particular item of the
factor "do you think that the healthcare personnel took care of you and your
child?" may have been interpreted in the same sense as the question
measuring DV. This particular item has a phi correlation of .61 with DV and
also very few responses in one cell. Should I try removing this item,
calculate the factor score again, dichotomize and look at the changed odds
ratio ?



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